Lalit Garg (editor) - Artificial Intelligence in Healthcare

This series covers monographs, both authored and edited, conference proceedings and novel engineering literature related to technology enabled solutions in the area of Humanitarian and Philanthropic empowerment. The series includes sustainable humanitarian research outcomes, engineering innovations, material related to sustainable and lasting impact on health related challenges, technology enabled solutions to fight disasters, improve quality of life and underserved community solutions broadly. Impactful solutions fit to be scaled, research socially fit to be adopted and focused communities with rehabilitation related technological outcomes get a place in this series. The series also publishes proceedings from reputed engineering and technology conferences related to solar, water, electricity, green energy, social technological implications and agricultural solutions apart from humanitarian technology and human centric community based solutions.

Major areas of submission/contribution into this series include, but not limited to: Humanitarian solutions enabled by green technologies, medical technology, photonics technology, artificial intelligence and machine learning approaches, IOT based solutions, smart manufacturing solutions, smart industrial electronics, smart hospitals, robotics enabled engineering solutions, spectroscopy based solutions and sensor technology, smart villages, smart agriculture, any other technology fulfilling Humanitarian cause and low cost solutions to improve quality of life.

More information about this series at http://www.springer.com/series/10038

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This book highlights the analytics and optimization issues in healthcare systems, proposes new approaches, and presents applications of innovative approaches in real facilities. In the past few decades, there has been an exponential rise in the application of artificial intelligence for solving complex and intricate problems arising in healthcare. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas.

The present book includes only nine chapters having the applications of intelligent algorithms in healthcare.

The first chapter by Malhan et al. addressed the current challenging problem of COVID-19. This chapter focuses on collecting unstructured data from Twitter, present in tweets and extract opinions including sentiments of people from all over the world, and applying a machine learning model to test the validity of Sentiments. In addition to the Sentiment Analysis, this research also provides the Geo-spatial analysis using Python, demonstrating the countries from where the outbreak and lockdown affected lives as well as the rising number of responses to the pandemic that were expressed country-wise via Twitter. In the chapter , Bhardwaj and Mittal delivered in-depth details about the applications of deep learning and swarm intelligence algorithms for image-based cancer recognition and diagnosis.

The book is edited to serve a broad readership, including computer scientists, medical professionals, and mathematicians interested in studying tools and techniques for computational intelligence and applications in healthcare. It will also be helpful for researchers, graduate, and undergraduate students with an interest in the fields of Artificial Intelligence and Healthcare.